I am an assistant professor of political communication at Louisiana State University's Manship School of Mass Communication. This site is where I bring together my love for studying politics, my love for analyzing data, and my love for the state of Louisiana.

Nov 16 Election 2016: Everything Old is New Again

On its face, Donald Trump’s win in Louisiana looks fairlytypical for the state. He took about the same share of the vote in the state as the previous Republican nominee, Mitt Romney, and carried the exact same 54 parishes. In fact, Trump’s 58.1 percent of the vote is pretty close to the average vote share in Louisiana for all Republican presidential nominees from 2000 to 2012 (57 percent). One could hardly be blamed for believing the results in Louisiana have little new to teach us.

Dig just a little deeper, however, and the results in Louisiana offer four lessons not only about the 2016 election but also about what happened beyond the borders of the state and what may unfold in the future.

1. Trump gained ground in the Midwest, but he lost ground in the South.

Trump took less of the southern vote than Romney did four years ago. He won the region by capturing 52.5 percent of all votes cast in the 11 states of the former confederacy and carrying ten of them, but his vote share fell 1.6 percentage points below Romney’s.

Contrast this with the Midwest (plus Pennsylvania) where Trump’s vote share exceeded Romney’s by two percentage points. He bested Romney’s performance in almost all the states in the region.

The pattern in the South is more fragmented. The Republican vote share remained pretty much the same in five states, including Louisiana, but slipped in three and rose in three others.

Declines in Texas, Virginia, and Georgia result in overall slip for Trump in South relative to Romney in 2012. Values are the percentage point change in the Republican vote share from 2012 to 2016. Estimates are based on vote counts as of Monday, Nov. 14, as reported by the New York Times.

The latter group includes Alabama and Mississippi, states with demographic profiles similar to Louisiana. All three are among the states with the highest shares of African Americans and people living in poverty, as well as the states with the fewest college degrees and lowest median household incomes. They also share a similar political climate and history.

Yet, among these three deepest of Deep South states, only Louisiana did not support Trump substantially more than Romney. Instead, states like Pennsylvania and Michigan – not Louisiana – match the trends in Alabama and Mississippi. Why?

2. Trump lost (some) support in Louisiana’s suburban parishes.

One factor that distinguishes Louisiana from Alabama and Mississippi is the share of the population living in rural areas. Louisiana’s population is much less rural (26.8 percent) than Alabama’s (41.0 percent) or Mississippi’s (50.7 percent). This matters.

Although the stereotypes of southern Republicans may point in a different direction, the party’s initial bulkheads in the region sixty years ago were metropolitan areas with well-to-do whites. Indeed, higher socio-economic white voters in the metro areas of New Orleans and Shreveport made Louisiana competitive for Republican presidential candidates for the first time in the 1950s.

Today, the Republican coalition in Louisiana and other southern states is more geographically diverse. It joins (mostly white) voters in rural parishes, like LaSalle or Cameron, with (mostly white) voters in suburban parishes, like St. Tammany and Jefferson.

That coalition held in 2016. Whether rural or suburban, all the parishes that went for Romney in 2012 also went for Trump in 2016.

However, the shift in the Republican vote share between those elections highlights the differences between the rural and urban ‘red’ parishes. Trump performed worse than Romney in nine Louisiana parishes. Almost all of these (except East Carroll) are among the most populous parishes in the state.

Trump did worse than Romney in more populous parishes. Values on the vertical axis are the percentage point change in the Republican vote share from 2012 to 2016. Red dots represent parishes Trump won. Blue dots represent parishes Clinton won. Election data reported by the Louisiana Secretary of State. Population data are from the U.S. Census's American Community Survey 2014 5-year average.

Three of the remaining eight are urban parishes where blacks make up 46 percent or more of the population: Caddo, East Baton Rouge, and Orleans.

The remaining five parishes where Trump lost ground have large shares of white suburban voters: Ascension (-0.2), Bossier (-0.6), Lafayette (-1.3), St. Tammany (-2.0), and Jefferson (-2.9). There has been slow change in the racial demographics of these parishes over longer stretches of time, but very little change in their racial profiles since 2012. For example, Jefferson Parish’s white population declined by six percentage points between 2000 and 2012, but has not budged since. Therefore, the shifts in Republican vote share more likely reflect changes (albeit relatively small) in the political behavior of the white populations of these parishes.

3. What Trump did in the Midwest has been unfolding in Louisiana for decades.

Aside from modest dips in suburban support, the election results in Louisiana are fairly typical for the state. More interesting is the fact that what happened in Pennsylvania and Midwestern states is also typical for Louisiana. In the Midwest and Pennsylvania, Trump’s largest gains over Romney came in counties with larger shares of rural whites and larger shares of whites without a college degree. The latter measure is a common but imperfect proxy for measuring socio-economic class.

Trump's strongest gains in Louisiana were also in parishes where larger shares of the white population do not have a college degree, which substantially overlaps with parishes with larger shares of rural whites.

Trump outperformed Romney in parishes where a larger share of whites do not have a college degree. Values on the vertical axis are the percentage point change in the Republican vote share from 2012 to 2016. Election data reported by the Louisiana Secretary of State. Population data are from the U.S. Census's American Community Survey 2014 5-year average.

But whereas the shift may have come as a surprise in Pennsylvania or Michigan, it has been unfolding for decades in Louisiana. In fact, in each presidential election since 1996, the statistical association between the share of whites without a college degree in a parish and the Republican vote share in the parish has grown stronger. This is depicted by the increasingly steep line across elections in the graph below.

The relationship between the share of whites without a college degree and the Republican vote share has strengthened over the past twenty years. Values on the vertical axis are the share of the vote won by Republican presidential candidates. Election data reported by the Louisiana Secretary of State. Demographics drawn from U.S. Census data most proximate in time to the election (2000 decennial census for 2000 and 2004; American Community Survey 2009 5-year average for the 2008 election; American Community Survey 2012 5-year average for the 2012 election; and American Community Survey 2014 5-year average for the 2016 election).

Bob Dole lost the total vote from parishes where more than 80 percent of whites did not have a college degree. Then in 2000, George W. Bush won 54 percent of the votes in parishes where that share of whites did not have a college degree. Eight years later, John McCain won 64 percent of those votes. Another eight years later and Trump won 68 percent of that vote.

It is important to remember that we are looking at geographical units here and not individual voters, and inferences about the former cannot tell us exactly what's going on with the latter. It is also worth remembering that discussions of groups of voters can sometimes obscure interesting variation.

4. “The past is never dead. It isn’t even past.”

So, Trump’s votes in Louisiana reflect a mix of something new with his slip in white suburban Republican parishes and something that has been unfolding for a while with his continued gains in white rural parishes.

It may also be a throwback to even older voting patterns in the state. To get a sense of how similar the 2016 election is to past presidential elections in Louisiana, I computed the correlation coefficients for Trump’s parish-level vote shares in 2016 and the Republican parish-level vote shares in each of the previous 13 presidential elections.

The correlation coefficient is a statistical tool that measures both the direction and the strength of a relationship between two variables (in this case, Trump’s share of the vote in a parish and a previous Republican candidate’s share of the vote there). Values of the correlation coefficient range from -1 to 1. Values above zero indicate a positive relationship between the variables (i.e., the value one variable tends to be higher when the value of the other variable is higher) and values below zero indicating a negative relationship (i.e., the value of one variable tends to be lower when the value of the other variable is higher). A correlation coefficient of zero would mean there is no relationship at all between the variables. The further the value from zero, the stronger the relationship.

Wallace support in 1968 does better than Reagan's support in 1980 to predict Trump support in 2016. Values on the vertical axis are the bivariate correlation coefficient between Trump's support in Louisiana's parishes in 2016 and each previous Republican candidate's support since 1964 (red) as well as Wallace's third-party support in 1968 (green). Election data for 2016 reported by the Louisiana Secretary of State. Data from previous elections are from Dave Leip's Atlas of U.S. Presidential Elections.

The results plotted with the red line in the chart below are unsurprising. With two exceptions – the reelection campaigns of Richard Nixon in 1972 and Ronald Reagan in 1984 – there is a steady drop off in the association between Trump’s performance and past Republicans the further back in time you look. If we think voting patterns change relatively slowly over time, then we should expect Trump’s vote share in 2016 to look a lot more like Romney’s vote share four years ago than Gerald Ford’s forty years ago.

One way to think about this is that you would be able to make a very good guess about where Trump did well and where he did poorly in 2016 based on how Bush, McCain, or Romney performed. Your guess would be a lot worse you were going off Reagan’s performance in 1980, George H.W. Bush’s performance in 1988 and 1992, or Dole’s in 1996. If you tried to predict Trump’s performance throughout the state based on how Barry Goldwater did in 1964, Nixon did in 1968, or Ford did in 1976 – well, you should not even bother.

This does not means there are no similarities between how Louisiana voted in the 1960s and how they voted this year. Looking beyond Republicans to the third-party candidacy of George Wallace the relationship is relatively strong with a correlation coefficient of 0.64. You would be able to do a decent job of guessing where Trump did better and worse just by knowing where Wallace did better and worse; indeed, you would be more accurate than if you tried to guess from Reagan’s votes in 1980.

Wallace ran a populist, anti-establishment campaign appealing to white voters particularly in rural areas, often with rhetoric stoking racial resentments and fears. He won Louisiana with 48 percent of the vote (his third best state after Alabama and Mississippi), but he also managed to get over ten percent in states like Michigan and Indiana.

I study politics. I live in Louisiana.

I write about Louisiana Politics

I am an assistant professor of political communication at Louisiana State University's Manship School of Mass Communication. This site is where I bring together my love for studying politics, my love for analyzing data, and my love for the state of Louisiana. This is my personal blog. The views expressed here are my own as are the errors.